Chasing artificial intelligence in shared socioeconomic pathways


Long-term scenarios play a pivotal role in climate research. In this commentary for One Earth, Mistra Geopolitics Co-Director Henrik Carlsen, Björn Nykvist, Somya Joshi and Fredrik Heintz focus on the need to better integrate emerging technologies in the Shared Socioeconomic Pathways (SSPs) – notably artificial intelligence (AI).

Photo: Gerd Altmann / Pixabay.
AI and socioeconomic pathways. Photo: Gerd Altmann / Pixabay

Climate change and its impacts extend far into the future, and therefore long-term perspectives are important for taking urgent climate action today and planning for both short and long-term time horizons. Therefore, climate scientists develop scenarios that describe the many possible ways in which society could develop in the coming decades. Due to high uncertainty, such scenarios are not predictive; developing credible scenarios over longer time perspectives is challenging, and has become even more so with recent breakthroughs in AI.

The authors argue that AI already shapes societal development and might have outsized impacts during the SSP time-frame. Given that AI could impact all drivers in the SSPs, it therefore has considerable potential to fundamentally change societies in ways important for research and policy.

Key messages

  • The development of artificial intelligence has likely reached an inflection point
  • AI has the potential to be a driver of strong societal change
  • All key elements of the Shared Socioeconomic Pathways will soon be impacted by AI
  • AI as a tool might hold the potential to aid attempts to build better scenarios


Given the pace of change, AI could quickly render today’s scenarios obsolete. In this commentary, the researchers discuss how the challenge of integrating the development of AI in future scenarios could be addressed. Read the commentary for One Earth.


Carlsen, H., Nykvist, B., Joshi, S., & Heintz, F. (2024). Chasing artificial intelligence in Shared Socioeconomic Pathways. One Earth DOI:

Authors of this publication

Björn Nykvist , Fredrik Heintz , Henrik Carlsen , Somya Joshi ,